Multiobjective Optimum Path Algorithm for Passenger Pretrip Planning in Multimodal Transportation Networks

Aifadopoulou, Georgia; Ziliaskopoulos, Athanasios; Chrisohoou, Evangelia

doi:10.3141/2032-04

Cited by 31 publications

(25 citation statements)

References 18 publications

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“…Generally, the mathematical formula of M-SPP with switching delay is very complicated (e.g., Ayfadopoulou et al 2007). In this paper, a simple mathematical formula of this problem is given.…”

Section: Introductionmentioning

confidence: 99%

Toward algorithms for multi-modal shortest path problem and their extension in urban transit network

Liu

Yang

2014

J Intell Manuf

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This paper investigates the algorithms of the multi-modal shortest path problem (M-SPP) under static and certain environment and their extension in urban transit network (UTN). The related M-SPP is one of the important and practical problems in several fields such as urban transportation system and freight transportation. Existing algorithms of various M-SPP are usually based on building a new network in terms of the hypergraph or transfer graph and implemented by extending the label correcting algorithm and label setting algorithm (LSA) in such a new network. The UTN is composed of multiple modes (e.g., automobile, bus, subway, light rail, pedestrian and so on) and, to get their destination, the users can alternate between different modes. As a special demand, the time-window is usually correlated with the M-SPP. In contrast to the algorithms for the classical M-SPP, the algorithms for the M-SPP in UTN are much complicated, particularly, these for the M-SPP with the switching delay and arriving time-window. In this paper, we consider the M-SPP with switching delay and that with both of the switching delay and arriving time-window. Firstly, a new approach is adopted to simplify the mathematical formulas of thes M-SPP with switching delay and then an improved LSA for the M-SPP with switching delay in the UTN is proposed. Afterwards, a reverse LSA is given to solve the M-SPP with both of switching delay and arriving time-window in the UTN. Finally, some examples are given to illustrate the labeling process of the designed algorithms.Keywords Shortest path problem (SPP) · Multi-modal shortest path problem (M-SPP) · Time-window · Label correcting algorithm (LCA) · Label setting algorithm (LSA)

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Section: Introductionmentioning

confidence: 99%

Toward algorithms for multi-modal shortest path problem and their extension in urban transit network

Liu

Yang

2014

J Intell Manuf

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“…In this case, the modes associated with the travel arcs are: Private modes, public rail modes (metro and train) and public surface modes (bus and collective taxi). To evaluate the objective parameters, data within tables 1 and 2 are processed with relations (11)(12)(13)(14)(15). The weights of the decision criteria w j are assessed by three experts, using the following Linguistic Variables: Very Low : VL =(0, 0.1, 0.…”

Section: Case Studymentioning

confidence: 99%

“…Many works have been treated the SPP in MTN. An overview of this literature can be found in [13,19,18] [10,17,4,5] [15,20] [22,6] [16,7]. In this type of problem, three constraints are considered.…”

Section: Introductionmentioning

confidence: 99%

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A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

Yamani¹,

Mouncif²,

Rida³

2014

ijco

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The paper must have abstract. In this paper, we present a fuzzy shortest path algorithm in Multimodal Transportation Networks (MTN). To extend the classical problem of shortest path, an innovative framework is presented, which integrates Fuzzy Logic and Multi Criteria Decision Making (MCDM) techniques. The aim is to deal with an efficient design for the multimodal shortest path computation taking into accounts not only the expected travel time, but also additional constraints such as: delays at mode and arc switching points, costs, viability of the sequence of the used modes and the number of modal transfers. To this scope, all previously mentioned constraints are evaluated following a new approach based on Fuzzy Logic and aggregated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to find the shortest path in MTN. A numerical example is also presented to demonstrate the computational process of the proposed approach.

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“…The routing problem is one of the classic problems in network analysis and Geographical Information Sciences (GIS), which has been the subject of much research (Aifadopoulou et al, 2007;Berube et al, 2006, Kramer et al, 2006Chiu and Rizos, 2012). Multi-objective methods can incorporate different objectives and preferences of users and are consequently more acceptable.…”

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confidence: 99%

Performance Comparison between the Multi-Colony and Multi-Pheromone ACO Algorithms for Solving the Multi-objective Routing Problem in a Public Transportation Network

Faroqi

Mesgari

2015

J. Navigation

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Routing in a multimodal urban public transportation network, according to the user's preferences, can be considered as a multi-objective optimisation problem. Solving this problem is a complicated task due to the different and incompatible objective functions, various modes in the network, and the large size of the network. In this research, two optimisation algorithms are considered for solving this problem. The multi-colony and multi-pheromone Ant Colony Optimisation (ACO) algorithms are two different modes of the Multi-Objective ACO (MOACO) algorithm. Moreover, according to the acquired information, the algorithms implemented in the public transportation network of Tehran consist of four modes. In addition, three objective functions have been simultaneously considered as the problem's objectives. The algorithms are run with different initial parameters and afterwards, the results are compared and evaluated based on the different obtained routes and with the aid of the convergence and repeatability tests, diversity and convergence metrics.2. Route planning. 3. Optimisation. 4. User-friendly. 5. Public transportation.

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Multiobjective Optimum Path Algorithm for Passenger Pretrip Planning in Multimodal Transportation Networks

Cited by 31 publications

References 18 publications

Toward algorithms for multi-modal shortest path problem and their extension in urban transit network

Toward algorithms for multi-modal shortest path problem and their extension in urban transit network

A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

Performance Comparison between the Multi-Colony and Multi-Pheromone ACO Algorithms for Solving the Multi-objective Routing Problem in a Public Transportation Network

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